scholarly journals Quectures: Personalised constructive learning in lectures

2018 ◽  
Vol 21 (3) ◽  
pp. 217-231 ◽  
Author(s):  
Heather A McQueen ◽  
Craig McMillan
Keyword(s):  
Academic Performance ◽  
Active Learning ◽  
Student Attitudes ◽  
Learning Strategy ◽  
Interactive Learning ◽  
Constructive Learning ◽  
Traditional Lectures ◽  
The Individual ◽  
Future Work ◽  
Fine Tune

Active learning exercises engage students during lectures, but often fail to take account of the individual learning position of each student. The ‘quecture’ is a partially flipped lecture that incorporates students posing their own questions (quecture questions), discussing them during lectures and revisiting them later. These interactive learning events are designed to personalise students’ construction of learning during lectures. Quectures were trialled in direct comparison with both fully flipped and traditional lectures, providing information on student attitudes, experiences and engagement with the learning strategy. Quectures were favoured by participants over the two other lecture formats and were found to be helpful both in increasing learning and in improving study habits, although some students had difficulty adjusting to, or disliked, the new mode of learning. The student-posed questions were also perceived by students to improve enquiry skills and to personalise learning. Although many chose not to engage with the strategy, those who did felt more engaged with, and more responsible for their own learning during quectures than in traditional lectures. Future work will be required to generalise the effectiveness of this strategy as well as to fine tune for optimum benefit. It will also be important to investigate which subpopulations of students preferentially engage or disengage with the strategy, and to unpick any relationship between this engagement and academic performance.

scholarly journals Enhancing generic capabilities and metacognitive awareness of first-year nursing students using active learning strategy

BMC Nursing ◽  
2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Carmen Wing Han Chan ◽  
Fiona Wing Ki Tang ◽  
Ka Ming Chow ◽  
Cho Lee Wong
Keyword(s):  
Nursing Education ◽  
Nursing Students ◽  
Active Learning ◽  
Flipped Classroom ◽  
Learning Strategy ◽  
Interactive Learning ◽  
Metacognitive Awareness ◽  
University Education ◽  
Strong Impact ◽  
Active Learning Strategy

Abstract Background Developing students’ generic capabilities is a major goal of university education as it can help to equip students with life-long learning skills and promote holistic personal development. However, traditional didactic teaching has not been very successful in achieving this aim. Kember and Leung’s Teaching and Learning Model suggests an interactive learning environment has a strong impact on developing students’ generic capabilities. Metacognitive awareness is also known to be related to generic capability development. This study aimed to assess changes on the development of generic capabilities and metacognitive awareness after the introduction of active learning strategy among nursing students. Methods This study adopted a quasi-experimental single group, matched pre- and posttest design. It was conducted in a school of nursing at a university in Hong Kong. Active learning approaches included the flipped classroom (an emphasis on pre-reading) and enhanced lectures (the breaking down of a long lecture into several mini-lectures and supplemented by interactive learning activities) were introduced in a foundational nursing course. The Capabilities Subscale of the Student Engagement Questionnaire and the Metacognitive Awareness Inventory were administered to two hundred students at the start (T0) and at the end of the course (T1). A paired t-test was performed to examine the changes in general capabilities and metacognitive awareness between T0 and T1. Results A total of 139 paired pre- and post-study responses (69.5 %) were received. Significant improvements were observed in the critical thinking (p < 0.001), creative thinking (p = 0.03), problem-solving (p < 0.001) and communication skills (p = 0.04) with the implementation of active learning. Significant changes were also observed in knowledge of cognition (p < 0.001) and regulation of cognition (p < 0.001) in the metacognitive awareness scales. Conclusions Active learning is a novel and effective teaching approach that can be applied in the nursing education field. It has great potential to enhance students’ development of generic capabilities and metacognitive awareness.

USING RESPONSE SYSTEM THROUGH VOTING IN PEER INSTRUCTION FOR LEARNING SUSTAINABILITY

2015 ◽  
Vol 77 (13) ◽  
Author(s):  
Bosede I. Edwards ◽  
Baharuddin Aris ◽  
Nurbiha A. Shukor ◽  
Hasnah Mohammed
Keyword(s):  
Active Learning ◽  
Student Performance ◽  
Peer Instruction ◽  
Performance Tests ◽  
Science Classrooms ◽  
Education Class ◽  
Traditional Lectures ◽  
Improved Learning ◽  
Automated Feedback ◽  
The Individual

Sustainable education must employ strategies that promote lifelong and meaningful learning. Peer Instruction (PI) is an active learning pedagogy specifically designed to achieve this. There are a number of elements involved in the various steps of the PI pedagogy which contributes to its effectiveness. However, most research studies reported in Peer Instruction focused on its use in science education and mainly on the whole pedagogy. The significance of the individual elements of the model have not been fully explored. Reports are also scarce on the use and benefits of PI in non-science classrooms. This study evaluates the pedagogical benefits of one of the elements of the PI model; the use of automated feedback based on students’ voting. 42 students in a postgraduate teacher education class were taken through sessions of Peer Instruction and traditional lectures; learning outcomes were compared in terms of student performance and student engagement and motivation. Performance tests (pre-tests and post-tests), live classroom observations and students’ reflections were monitored to determine the level of performance and engagement. Results show that students reported increased interest, motivation and engagement and the ability of the voting sessions to foster metacognition. Active learning and learning readiness were also emphasized while the lecture sessions were reported as normal or usual. The result validates the usefulness of voting component of the PI model for fostering improved learning; noting that students are able to benefit more from personal evaluation when voting results are displayed after voting.

scholarly journals Using Cmap Cloud in the cooperative development of interactive concept maps to improve academic performance

2018 ◽  
Vol 9 ◽  
pp. 1474-1479
Author(s):  
Ignasi Navarro Soria ◽  
Carlota González Gómez ◽  
Fernando López Becerra ◽  
Francisco Fernández Carrasco ◽  
Jorge Heliz Llopis
Keyword(s):  
Academic Performance ◽  
Concept Maps ◽  
Learning Strategy ◽  
Study Strategies ◽  
Cooperative Work ◽  
Control Group ◽  
Individual Level ◽  
The Individual ◽  
Teaching Learning ◽  
Experimental Group

For this study, 148 students were recruited, and they consisted of two experimental groups and one control group. Both experimental groups were instructed in the development of conceptual maps using the CmapTools software, while the students in the control group freely chose which study strategies they would use to acquire the knowledge that would be evaluated. The difference between the two experimental groups was that one of the experimental groups followed the guidelines of a cooperative activity, developing a conceptual map in work teams (4 students to each team) using CmapCloud, while in the other experimental group, each student developed the contents of a conceptual map in CmapTools on an individual level. The objective was to detect whether there would be any statistically significant differences between the three groups at the level of academic performance. For this purpose, the same sample was tested by means of the same type of knowledge acquisition test. The data obtained reveal that the scores are higher in the experimental groups than in the control group, and in turn, the experimental group that included cooperative work obtained a better level of performance than the experimental group that worked at the individual level. Therefore, we conclude that simple modifications in the pedagogical strategy (introducing an effective learning strategy and cooperative work), would significantly improve the teaching-learning process and, consequently, would significantly improve the average performance of the students.

THE EFFECT OF LEARNING STRATEGY ON MATHEMATICS LEARNING OUTCOMES IN CLASS IV STUDENTS AT PRIMARY SCHOOL 09 KABA WETAN

2020 ◽  
Vol 3 (1) ◽  
pp. 67-83
Author(s):  
Ahmad Abdul Rochim ◽  
Siti Bandiah
Keyword(s):  
Learning Outcomes ◽  
Learning Strategies ◽  
Design Research ◽  
Learning Strategy ◽  
Interactive Learning ◽  
Mathematics Learning ◽  
Problem Based Learning ◽  
Sampling Technique ◽  
Analysis Technique ◽  
Class Iv

The accuracy in choosing a learning strategy is a very important part in efforts to improve the achievement of student learning outcomes. Therefore this study aims to determine the effect of learning strategies on mathematics learning outcomes. This study uses a 2x2 factorial design research. Through this design the effects of Interactive learning strategies and problem-based learning will be compared to student mathematics learning outcomes. The population in this study were all students of grade IV SDN 09 Kaba Wetan, totaling 76 students, consisting of 2 classes. To determine the sample class, a random sampling technique is used. The sample classes used were 2 classes totaling 76 students, class IV-A as an Interactive class and class IV-B as a problem-based class. The data analysis technique used is descriptive and inferential statistical techniques. And testing the analysis requirements is the normality test using the Lilifors Test, while the homogeneity requirements are using the F Test and Barlett Test. After testing the analysis requirements, the two-way variance analysis of Analilsis is performed. The results of this study indicate that there is an interaction effect between learning strategies on student mathematics learning outcomes. So that the selection of appropriate learning strategies is influenced by the ability of teachers to understand the characteristics of their students. In the learning strategy applied by the teacher can optimize student mathematics learning outcomes by choosing class strategies namely Interactive learning and problem based learning classes.

An Active Learning Approach to Teaching Social Determinants of Health

2020 ◽  
Vol 6 (4) ◽  
pp. 266-273
Author(s):  
Jeanita W. Richardson
Keyword(s):  
Active Learning ◽  
Learning Style ◽  
Social Determinants ◽  
Learning Approach ◽  
Learning Style Preferences ◽  
Open Discussion ◽  
Approach To Teaching ◽  
The Individual ◽  
Style Preferences ◽  
The Impact

This active learning exercise is designed to deconstruct the impact of social determinants through the assumption of randomly selected personas. As an active learning exercise, it provides opportunities for discussion, problem solving, writing, and synthesis, while incorporating multiple learning style preferences. Part 1 involves assessing the individual social determinants at work. Part 2 involves exploring ways said determinants can enhance community health through collaboration. Assumption of personas unlike one’s own facilitates an open discussion of social position and ranges of factors influential to health without potentially evoking a sense of defensiveness associated with personal privilege (or the lack thereof).

scholarly journals Between Level Up and Game Over: A Systematic Literature Review of Gamification in Education

2021 ◽  
Vol 13 (4) ◽  
pp. 2247 ◽  
Author(s):  
Ana Manzano-León ◽  
Pablo Camacho-Lazarraga ◽  
Miguel A. Guerrero ◽  
Laura Guerrero-Puerta ◽  
José M. Aguilar-Parra ◽  
...  
Keyword(s):  
Systematic Review ◽  
Academic Performance ◽  
Game Design ◽  
Learning Strategy ◽  
Experimental Studies ◽  
Quasi Experimental ◽  
Current Lines ◽  
Meta Analyses ◽  
Game Elements ◽  
The Impact

Educational gamification consists of the use of game elements and game design techniques in the educational context. The objective of this study is to examine the existing evidence on the impact of educational gamification on student motivation and academic performance in the last five years in order to analyze its distribution over time, educational level, variables, and most used game elements, and know the advantages of its implementation in the classroom. For this, a systematic review is proposed through the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) methodology in three multidisciplinary databases, through an exhaustive search with inclusion and exclusion criteria on quantitative experimental studies that explore gamification in educational centers, which provide information about the most current lines of research. Fourteen studies were included in this review. These used experimental or quasi-experimental designs. Most of them report gamification as a valid learning strategy. The results support the conclusion that educational gamification has a potential impact on the academic performance, commitment, and motivation of students. Therefore, this study implies the need to expand research on the needs and challenges of students when learning with gamified techniques.

scholarly journals A transferable active-learning strategy for reactive molecular force fields

2021 ◽  
Author(s):  
Tom Young ◽  
Tristan Johnston-Wood ◽  
Volker L. Deringer ◽  
Fernanda Duarte
Keyword(s):  
Machine Learning ◽  
Active Learning ◽  
Learning Strategy ◽  
Force Fields ◽  
Molecular Simulations ◽  
Quantum Mechanical ◽  
Interatomic Potentials ◽  
Molecular Force ◽  
High Level ◽  
Active Learning Strategy

Predictive molecular simulations require fast, accurate and reactive interatomic potentials. Machine learning offers a promising approach to construct such potentials by fitting energies and forces to high-level quantum-mechanical data, but...

scholarly journals Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps

2021 ◽  
Author(s):  
Ali H. Al-Timemy ◽  
Nebras H. Ghaeb ◽  
Zahraa M. Mosa ◽  
Javier Escudero
Keyword(s):  
Transfer Learning ◽  
Learning Strategy ◽  
Clinical Decision ◽  
Topographic Maps ◽  
Computer Assisted ◽  
Clinical Knowledge ◽  
Average Accuracy ◽  
Assisted Diagnosis ◽  
Improved Accuracy ◽  
Fine Tune

Abstract Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision based on the fusion of probabilities. Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble-specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features. This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computer-assisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and to perform fast and accurate KCN treatment.

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